import paddle

# paddle 版本
print(paddle.__version__)

print('飞桨框架内置模型：', paddle.vision.models.__all__)
# 飞桨框架内置模型= ['ResNet', 'resnet18', 'resnet34', 'resnet50', 'resnet101', 'resnet152',
#                    'resnext50_32x4d', 'resnext50_64x4d', 'resnext101_32x4d', 'resnext101_64x4d',
#                    'resnext152_32x4d', 'resnext152_64x4d', 'wide_resnet50_2', 'wide_resnet101_2',
#                    'VGG', 'vgg11', 'vgg13', 'vgg16', 'vgg19', 'MobileNetV1', 'mobilenet_v1',
#                    'MobileNetV2', 'mobilenet_v2', 'MobileNetV3Small', 'MobileNetV3Large',
#                    'mobilenet_v3_small', 'mobilenet_v3_large', 'LeNet', 'DenseNet', 'densenet121',
#                    'densenet161', 'densenet169', 'densenet201', 'densenet264', 'AlexNet', 'alexnet',
#                    'InceptionV3', 'inception_v3', 'SqueezeNet', 'squeezenet1_0', 'squeezenet1_1',
#                    'GoogLeNet', 'googlenet', 'ShuffleNetV2', 'shufflenet_v2_x0_25', 'shufflenet_v2_x0_33',
#                    'shufflenet_v2_x0_5', 'shufflenet_v2_x1_0', 'shufflenet_v2_x1_5', 'shufflenet_v2_x2_0',
#                    'shufflenet_v2_swish']


# 模型组网并初始化网络
lenet = paddle.vision.models.LeNet(num_classes=10)

# 可视化模型组网结构和参数
paddle.summary(lenet, (1, 1, 28, 28))

